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A Combined MRI Biomarker Approach Using a Non-Standard Multiple Factor Analysis

机译:使用非标准多因素分析的组合MRI生物标志物方法

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In medical applications, various MRI biomarkers, which are extracted from different MRI modalities, are used to detect physiologic abnormalities but different biomarkers are usually sensitive to different aspects of the disease. Thus, it would be interesting to use the information carried by multiple biomarkers, especially in the context of clinical trials where the efficiency of a treatment should be judged as precisely as possible. This paper proposes an approach that combined various MRI biomarkers in the context of a Multiple Sclerosis (MS) clinical trial. The method mainly includes four steps: After extracting the biomarkers from different MRI modalities, a histogram analysis is performed followed by a Multiple Factor Analysis (MFA) to produce linear combinations of the MRI biomarkers and finally, a Hierarchical Clustering based on the MFA results is executed. The aim of this approach is to conclude more effectively on the effect of a treatment in a clinical trial.
机译:在医学应用中,从不同的MRI方式中提取的各种MRI生物标记物被用于检测生理异常,但是不同的生物标记物通常对疾病的不同方面敏感。因此,使用多个生物标记物携带的信息将是有趣的,尤其是在临床试验中,应尽可能准确地判断治疗的有效性。本文提出了一种在多发性硬化症(MS)临床试验中结合多种MRI生物标记物的方法。该方法主要包括四个步骤:从不同的MRI方式中提取生物标志物后,进行直方图分析,然后进行多因素分析(MFA)以产生MRI生物标志物的线性组合,最后,基于MFA结果进行层次聚类是被执行。这种方法的目的是在临床试验中更有效地得出治疗效果的结论。

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